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. 2024;16(1):529-552.
doi: 10.1159/000542420. Epub 2024 Dec 3.

Complex Thrombo-Inflammatory Responses versus Outcomes of Non-COVID-19 Community-Acquired Pneumonia and COVID-19

Greg Haljan  1 , Terry Lee  2 , Anne McCarthy  3 , Juthaporn Cowan  3 , Jennifer Tsang  4   5 , Francois Lelouche  6 , Alexis F Turgeon  7   8 , Patrick Archambault  9   10 , Francois Lamontagne  11 , Robert Fowler  12 , Jennifer Yoon  13 , Peter Daley  14 , Matthew P Cheng  15 , Donald C Vinh  15 , Todd C Lee  15 , Karen C Tran  16 , Brent W Winston  17 , Hyejin Julia Kong  18 , John H Boyd  18   19 , Keith R Walley  18   19 , Allison McGeer  20   21 , David M Maslove  22 , John C Marshall  23 , Joel Singer  2 , Fagun Jain  24 , James A Russell  18   19
Affiliations

Complex Thrombo-Inflammatory Responses versus Outcomes of Non-COVID-19 Community-Acquired Pneumonia and COVID-19

Greg Haljan et al. J Innate Immun. 2024.

Abstract

Introduction: The thrombo-inflammatory response and outcomes of community-acquired pneumonia (CAP) due to various organisms (non-COVID-19 CAP) versus CAP due to a single virus, SARS-CoV-2 (i.e., COVID-19) may differ.

Methods: Adults hospitalized with non-COVID-19 CAP (December 1, 2021-June 15, 2023) or COVID-19 (March 2, 2020-June 15, 2023) in Canada. We compared non-COVID-19 CAP and COVID-19 baseline, thrombo-inflammatory response, and mortality. We measured plasma cytokine and coagulation factor levels in a sample of patients, did hierarchical clustering, and compared cytokine and coagulation factor levels.

Results: In 2,485 patients (non-COVID-19 CAP, n = 719; COVID-19 patients, n = 2,157), non-COVID-19 CAP patients had significantly lower 28-day mortality (CAP vs. COVID-19 waves 1 and 2; 10% vs. 18% and 16%, respectively), intensive care unit admission (CAP vs. all waves; 15% vs. 39%, 37%, 33%, and 24%, respectively), invasive ventilation (CAP vs. waves 1, 2, and 3 patients; 11% vs. 25%, 20%, and 16%), vasopressor use (CAP 12% vs. 23%, 21%, and 18%), and renal replacement therapy use (CAP 3% vs. Omicron 7%). Complexity of hierarchical clustering aligned directly with mortality: COVID-19 wave 1 and 2 patients had six clusters at admission and higher mortality than non-COVID-19 CAP and Omicron that had three clusters at admission. Pooling all COVID-19 waves increased complexity with seven clusters on admission.

Conclusion: Complex thrombo-inflammatory responses aligned with mortality of CAP. At a fundamental level, the human thrombo-inflammatory response to a brand new virus was "confused" whereas humans had eons of time to develop a more concise efficient thrombo-inflammatory host response to CAP.

Keywords: COVID-19; Coagulation factors; Community-acquired pneumonia; Cytokines; Hierarchical clustering; Mortality.

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Conflict of interest statement

Dr. Russell reports patents owned by the University of British Columbia (UBC) that are related to (1) the use of PCSK9 inhibitor(s) in sepsis, (2) the use of vasopressin in septic shock and (3) a patent owned by Ferring for use of selepressin in septic shock. Dr. Russell is an inventor on these patents. Dr. Russell was a founder, Director and shareholder in Cyon Therapeutics Inc. (now closed) and is a shareholder in Molecular You Corp. Dr. Russell is Senior Research Advisor of the British Columbia, Canada Post COVID – Interdisciplinary Clinical Care Network (PC-ICCN). Dr. Russell is no longer actively consulting for any industry. Dr. Russell reports receiving consulting fees in the last 3 years. Dr. Russell was a funded member of the Data and Safety Monitoring Board (DSMB) of an NIH-sponsored trial of plasma in COVID-19 (PASS-IT-ON) (2020–2021). Dr. Russell has received grants for COVID-19 and for pneumonia research: 4 from the Canadian Institutes of Health Research (CIHR) and 3 from the St. Paul’s Foundation (SPF). Dr. Russell was a non-funded Science Advisor and member, Government of Canada COVID-19 Therapeutics Task Force (June 2020–2021).

Figures

Fig. 1.
Fig. 1.
Comparison of non-COVID-19 CAP and COVID-19 waves 1, 2, 3, and Omicron wave patient outcomes. The following factors were accounted for in the adjusted analysis: age, sex, chronic cardiac disease, chronic kidney disease, hypertension, diabetes, chronic pulmonary disease, liver disease, chronic neurological disorder. Malignant neoplasm, chronic hematologic disease, obesity, rheumatologic disorder, and dementia. The indicated sample size was for the analysis of primary outcome – 28-day outcome. Sample size varied slightly across outcomes due to missing data. *Adjusted regression analysis was not feasible numerically as too few patients received RRT during the first 14 days.
Fig. 2.
Fig. 2.
Kaplan-Meier curves of non-COVID-19 CAP and COVID-19 waves 1, 2, 3, and Omicron wave patients by log-rank test. The numbers at risk table was provided beneath the Kaplan Meier curves.
Fig. 3.
Fig. 3.
Hierarchical clustering and heat maps of plasma cytokines and coagulation factors on day 0 and 4 in (a) COVID-19 waves 1 and 2, (b) Omicron wave, (c) pooled COVID-19-19 overall, and (d) non-COVID-19 CAP. Red is higher expression while blue is lower expression. Individual patients are the columns and individual rows are the cytokines and coagulation factors. Colors on the left indicate the individual clusters as determined by hierarchical clustering.
See this image and copyright information in PMC

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